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Bayesian Confidence Intervals for Multiplexed Proteomics Integrate Ion-Statistics with Peptide Quantification Concordance, part 2

ABSTRACT: This study presents a mathematically rigorous approach that integrates peptide MS-signal and peptide-measurement agreement into an estimation of the true protein ratio and the associated confidence.We call our method BACIQ (Bayesian Approach to Confidence Intervals for protein Quantitation – pronounced BASIC).

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human) Escherichia Coli

SUBMITTER: Meera Gupta

LAB HEAD: Martin wuehr

PROVIDER: PXD012285 | Pride | 2019-09-30

REPOSITORIES: Pride

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Bayesian Confidence Intervals for Multiplexed Proteomics Integrate Ion-statistics with Peptide Quantification Concordance.

Peshkin Leonid L Gupta Meera M Ryazanova Lillia L Wühr Martin M

Molecular & cellular proteomics : MCP 20190716 10

Multiplexed proteomics has emerged as a powerful tool to measure relative protein expression levels across multiple conditions. The relative protein abundances are inferred by comparing the signals generated by isobaric tags, which encode the samples' origins. Intuitively, the trust associated with a protein measurement depends on the similarity of ratios from the protein's peptides and the signal-strength of these measurements. However, typically the average peptide ratio is reported as the est ...[more]

PMID: 31311848

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